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Hydrogen embrittlement can result in a sudden failure in metallic materials, which is particularly harmful in industrially relevant alloys, such as steels. A more comprehensive understanding of hydrogen interactions with microstructural features is critical for preventing hydrogen-induced damage and promoting a hydrogen-based environment-benign economy. We use the Kelvin probe-based potentiometric hydrogen electrode method and thermal desorption spectroscopy to investigate hydrogen interactions with different hydrogen traps in ferritic FeCr alloys with different chromium contents, dislocation densities, and grain sizes. In addition, we confirm the validity of a novel nanohardness-based diffusion coefficient approach by performing in situ nanoindentation testing. Simultaneous acquisition of the dynamic time-resolved mechanical response of FeCr alloys to hydrogen and the hydrogen diffusivities in these alloys is possible during continuous hydrogen supply. Dislocations, grain boundaries and Cr atoms induce reversible hydrogen trapping sites in these ferritic alloys, leading to the reduction of the hydrogen diffusion coefficients and the increase of the absorbed hydrogen., Comment: 39 pages, 11 figures

Studying and controlling quantum many-body interactions is fundamentally important for quantum science and related emerging technologies. Optically addressable solid-state spins offer a promising platform for exploring various quantum many-body phenomena due to their scalability to a large Hilbert space. However, it is often challenging to probe many-body dynamics in solid-state spin systems due to large on-site disorder and undesired coupling to the environment. Here, we investigate an optically addressable solid-state spin system comprising a strongly interacting ensemble of millions of ytterbium-171 ions in a crystal. Notably, this platform features a clock transition that gives rise to pure long-range spin-exchange interactions, termed the dipolar XY model. Leveraging this unique feature, we investigate quantum thermalization by varying the relative ratio of interaction strength to disorder, dynamically engineering the XY model into other many-body Hamiltonian models, and realizing a time-crystalline phase of matter through periodic driving. Our findings indicate that an ensemble of rare-earth ions serves as a versatile testbed for many-body physics and offers valuable insights for advancing quantum technologies.

Accurate thermometry of laser-cooled ions is crucial for the performance of the trapped-ions quantum computing platform. However, most existing methods face a computational exponential bottleneck. Recently, a thermometry method based on bichromatic driving was theoretically proposed by Ivan Vybornyi et al. to overcome this obstacle, which allows the computational complexity to remain constant with the increase of ion numbers. In this paper, we provide a detailed statistical analysis of this method and prove its robustness to several imperfect experimental conditions using Floquet theory. We then experimentally verify its good performance on a linear segmented surface-electrode ion trap platform for the first time. This method is proven to be effective from near the motional ground state to a few mean phonon numbers. Our theoretical analysis and experimental verification demonstrate that the scheme can accurately and efficiently measure the temperature in ion crystals.

This paper presents Deformable Neural Vessel Representations (DeNVeR), an unsupervised approach for vessel segmentation in X-ray videos without annotated ground truth. DeNVeR uses optical flow and layer separation, enhancing segmentation accuracy and adaptability through test-time training. A key component of our research is the introduction of the XACV dataset, the first X-ray angiography coronary video dataset with high-quality, manually labeled segmentation ground truth. Our evaluation demonstrates that DeNVeR outperforms current state-of-the-art methods in vessel segmentation. This paper marks an advance in medical imaging, providing a robust, data-efficient tool for disease diagnosis and treatment planning and setting a new standard for future research in video vessel segmentation. See our project page for video results at https://kirito878.github.io/DeNVeR/., Comment: Project page: https://kirito878.github.io/DeNVeR/

Cobalt disilicide provides a promising nearly-epitaxial superconducting material on silicon, which is compatible with high-density integrated circuit technology. We have characterized CoSi$_{2}$ superconducting microwave cavities around 5.5 GHz for resonance frequency fluctuations at temperatures 10 - 200 mK. We found relatively weak fluctuations $(\delta f/f)^2$ following the spectral density $A/f^{\gamma} $, with $A \simeq 6 \times 10^{-16}$ and $\gamma$ slightly below 1 at an average number of photons of $10^4$; the noise decreased with measurement power as $1/P^{1/2}$. We identify the noise as arising from kinetic inductance fluctuations and discuss possible origins of such fluctuations., Comment: 6 pages, 3 figures

Single photon emitters with internal spin are leading contenders for developing quantum repeater networks, enabling long-range entanglement distribution for transformational technologies in communications and sensing. However, scaling beyond current few-node networks will require radical improvements to quantum link efficiencies and fidelities. Solid-state emitters are particularly promising due to their crystalline environment, enabling nanophotonic integration and providing spins for memory and processing. However, inherent spatial and temporal variations in host crystals give rise to static shifts and dynamic fluctuations in optical transition frequencies, posing formidable challenges in establishing large-scale, multipartite entanglement. Here, we introduce a scalable approach to quantum networking that utilizes frequency erasing photon detection in conjunction with adaptive, real-time quantum control. This enables frequency multiplexed entanglement distribution that is also insensitive to deleterious optical frequency fluctuations. Single rare-earth ions are an ideal platform for implementing this protocol due to their long spin coherence, narrow optical inhomogeneous distributions, and long photon lifetimes. Using two 171Yb:YVO4 ions in remote nanophotonic cavities we herald bipartite entanglement and probabilistically teleport quantum states. Then, we extend this protocol to include a third ion and prepare a tripartite W state: a useful input for advanced quantum networking applications. Our results provide a practical route to overcoming universal limitations imposed by non-uniformity and instability in solid-state emitters, whilst also showcasing single rare-earth ions as a scalable platform for the future quantum internet.

An ancient and counterintuitive phenomenon know as the Mpemba effect (water can cool faster when initially heated up) showcases the critical role of initial conditions in relaxation processes. How to realize and utilize this effect for speeding up relaxation is an important but challenging task in purely quantum system till now. Here, we report the first experiment, as far as we know,about the strong Mpemba effect in a single trapped ion system in which an exponentially expedited relaxation in time is observed by preparing an optimal initial state with no excitation of the slowest decaying mode. Also, we find that the condition of realizing such effect coincides with the Liouvillian exceptional point, featuring the coalescence of both the eigenvalues and the eigenmodes of the system. Our work provides an efficient strategy to exponentially accelerate relaxations of quantum system to their stationary state, and suggests a link unexplored yet between the Mpemba effect and the non-Hermitian physics. It could open up the door to engineer a wide range of dissipative quantum systems by utilizing the anomalous Mpemba effect, for applications in quantum simulation and quantum information processing.

We have looked into cobalt disilicide (CoSi$_2$) as a potential building block for superconducting quantum circuits. In order to achieve this, we annealed a thin layer of Co to create 10-105 nm thick microwave cavities from CoSi$_2$ embedded in the silicon substrate. The cavity properties were measured as a function of temperature and power. In films measuring 10 and 25 nm, we find a significant kinetic inductance $L_\mathrm{K}$ with a non-BCS power-law variation $\delta L_\mathrm{K} \propto T^{4.3 \pm 0.2}$ at low temperatures. The quality factor of the studied microwave resonances increased almost linearly with thickness, with two-level systems having very little effect. The power dependence of kinetic inductance was analyzed in terms of heat flow due to electron-phonon coupling, which was found stronger than estimated for heat relaxation by regular quasiparticles., Comment: 7 pages, 4 figures

Quantum sensing utilizing unique quantum properties of non-Hermitian systems to realize ultra-precision measurements has been attracting increasing attention. However, the debate on whether non-Hermitian systems are superior to Hermitian counterparts in sensing remains an open question. Here, we investigate the quantum information in PT-symmetric quantum sensing utilizing two experimental schemes based on the trapped-ion platform. It turns out that the existence of advantages of non-Hermitian quantum sensing heavily depends on additional information resources carried by the extra degrees of freedom introduced to construct PT-symmetric quantum sensors. Moreover, the practical application of non-Hermitian quantum sensing with superior performance is primarily restricted by the additional resource consumption accompanied by the post-selection. Our study provides theoretical references for the construction of non-Hermitian quantum sensors with superior performance and has potential applications in research fields of quantum precision measurement and quantum information processing., Comment: 16 pages, 7 figures

A nanophotonic waveguide coupled with an atomic array forms one of the strongly-coupled quantum interfaces to showcase many fascinating collective features of quantum dynamics. In particular for a dissimilar array of two different interparticle spacings with competing photon-mediated dipole-dipole interactions and directionality of couplings, we study the steady-state phases of atomic excitations under a weakly-driven condition of laser field. We identify a partial set of steady-state phases of the driven system composed of combinations of steady-state solutions in a homogeneous array. We also reveal an intricate role of the atom at the interface of the dissimilar array in determining the steady-state phases and find an alteration in the dichotomy of the phases strongly associated with steady-state distributions with crystalline orders. We further investigate in detail the interaction-induced depletion in half of the dissimilar array. This blockaded region results from two contrasting interparticle spacings near the reciprocal coupling regime, which is evidenced from the analytical solutions under the reciprocal coupling. Our results can provide insights in the driven-dissipative quantum phases of atomic excitations with nonreciprocal couplings and pave the avenues toward quantum simulations of exotic many-body states essential for quantum information applications., Comment: 6 figures

If the video has long been mentioned as a widespread visualization form, the animation sequence in the video is mentioned as storytelling for people. Producing an animation requires intensive human labor from skilled professional artists to obtain plausible animation in both content and motion direction, incredibly for animations with complex content, multiple moving objects, and dense movement. This paper presents an interactive framework to generate new sequences according to the users' preference on the starting frame. The critical contrast of our approach versus prior work and existing commercial applications is that novel sequences with arbitrary starting frame are produced by our system with a consistent degree in both content and motion direction. To achieve this effectively, we first learn the feature correlation on the frameset of the given video through a proposed network called RSFNet. Then, we develop a novel path-finding algorithm, SDPF, which formulates the knowledge of motion directions of the source video to estimate the smooth and plausible sequences. The extensive experiments show that our framework can produce new animations on the cartoon and natural scenes and advance prior works and commercial applications to enable users to obtain more predictable results., Comment: This paper has been accepted for publication on IEEE Transactions on Visualization and Computer Graphics (TVCG), January 2023. Project website: http://graphics.csie.ncku.edu.tw/SDPF

Atomic array coupled to a one-dimensional nanophotonic waveguide allows photon-mediated dipole-dipole interactions and nonreciprocal decay channels, which hosts many intriguing quantum phenomena owing to its distinctive and emergent quantum correlations. In this atom-waveguide quantum system, we theoretically investigate the atomic excitation dynamics and its transport property, specifically at an interface of dissimilar atomic arrays with different interparticle distances. We find that the atomic excitation dynamics hugely depends on the interparticle distances of dissimilar arrays and the directionality of nonreciprocal couplings. By tuning these parameters, a dominant excitation reflection can be achieved at the interface of the arrays in the single excitation case. We further study two effects on the transport property-of external drive and of single excitation delocalization over multiple atoms, where we manifest a rich interplay between multi-site excitation and the relative phase in determining the transport properties. Finally, we present an intriguing trapping effect of atomic excitation by designing multiple zones of dissimilar arrays. Similar to the single excitations, multiple excitations are reflected from the array interfaces and trapped as well, although complete trapping of many excitations together is relatively challenging at long time due to a faster combined decay rate. Our results can provide insights to nonequilibrium quantum dynamics in dissimilar arrays and shed light on confining and controlling quantum registers useful for quantum information processing., Comment: 8 figures

When H, the lightest, smallest and most abundant atom in the universe, makes its way into a high-strength alloy (>650 MPa), the material's load-bearing capacity is abruptly lost. This phenomenon, known as H embrittlement, was responsible for the catastrophic and unpredictable failure of large engineering structures in service. The inherent antagonism between high strength requirements and H embrittlement susceptibility strongly hinders the design of lightweight yet reliable structural components needed for carbon-free hydrogen-propelled industries and reduced-emission transportation solutions. Inexpensive and scalable alloying and microstructural solutions that enable both, an intrinsically high resilience to H and high mechanical performance, must be found. Here we introduce a counterintuitive strategy to exploit typically undesired chemical heterogeneity within the material's microstructure that allows the local enhancement of crack resistance and local H trapping, thereby enhancing the resistance against H embrittlement. We deploy this approach to a lightweight, high-strength steel and produce a high-number density Mn-rich zones dispersed within the microstructure. These solute-rich buffer regions allow for local micro-tuning of the phase stability, arresting H-induced microcracks thus interrupting the H-assisted damage evolution chain, regardless of how and when H is introduced and also regardless of the underlying embrittling mechanisms. A superior H embrittlement resistance, increased by a factor of two compared to a reference material with a homogeneous solute distribution within each microstructure constituent, is achieved at no expense of the material's strength and ductility.

Generating texts with a large language model (LLM) consumes massive amounts of memory. Apart from the already-large model parameters, the key/value (KV) cache that holds information about previous tokens in a sequence can grow to be even larger than the model itself. This problem is exacerbated in one of the current LLM serving frameworks which reserves the maximum sequence length of memory for the KV cache to guarantee generating a complete sequence as they do not know the output sequence length. This restricts us to use a smaller batch size leading to lower GPU utilization and above all, lower throughput. We argue that designing a system with a priori knowledge of the output sequence can mitigate this problem. To this end, we propose S$^{3}$, which predicts the output sequence length, schedules generation queries based on the prediction to increase device resource utilization and throughput, and handle mispredictions. Our proposed method achieves 6.49$\times$ throughput over those systems that assume the worst case for the output sequence length.

Stochastic block partitioning (SBP) is a community detection algorithm that is highly accurate even on graphs with a complex community structure, but its inherently serial nature hinders its widespread adoption by the wider scientific community. To make it practical to analyze large real-world graphs with SBP, there is a growing need to parallelize and distribute the algorithm. The current state-of-the-art distributed SBP algorithm is a divide-and-conquer approach that limits communication between compute nodes until the end of inference. This leads to the breaking of computational dependencies, which causes convergence issues as the number of compute nodes increases, and when the graph is sufficiently sparse. In this paper, we introduce EDiSt - an exact distributed stochastic block partitioning algorithm. Under EDiSt, compute nodes periodically share community assignments during inference. Due to this additional communication, EDiSt improves upon the divide-and-conquer algorithm by allowing it to scale out to a larger number of compute nodes without suffering from convergence issues, even on sparse graphs. We show that EDiSt provides speedups of up to 23.8X over the divide-and-conquer approach, and speedups up to 38.0X over shared memory parallel SBP when scaled out to 64 compute nodes.

We investigate speeding up of relaxation of Markovian open quantum systems with the Liouvillian exceptional point (LEP), where the slowest decay mode degenerate with a faster decay mode. The degeneracy significantly increases the gap of the Liouvillian operator, which determines the timescale of such systems in converging to stationarity, and hence accelerates the relaxation process. We explore an experimentally relevant three level atomic system, whose eigenmatrices and eigenspectra are obtained completely analytically. This allows us to gain insights in the LEP and examine respective dynamics with details. We illustrate that the gap can be further widened through Floquet engineering, which further accelerates the relaxation process. Finally, we extend this approach to analyze laser cooling of trapped ions, where vibrations (phonons) couple to the electronic states. An optimal cooling condition is obtained analytically, which agrees with both existing experiments and numerical simulations. Our study provides analytical insights in understanding LEP, as well as in controlling and optimizing dissipative dynamics of atoms and trapped ions.